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Improved Particle Filtering-Based Estimation of the Number of Competing Stations in IEEE 802.11 Networks

机译:基于改进的基于粒子滤波的IEEE 802.11网络中竞争站点数量的估计

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This letter proposes a new method to estimate the number of competing stations in IEEE 802.11 networks. Due to the nonlinearon-Gaussian nature of measurement model, a nonlinear filtering algorithm, called the Gaussian mixture sigma point particle filter (GMSPPF), is proposed herein to estimate the number of competing stations. Since GMSPPF represents a better alternative to the conventional extended Kalman filter (EKF), unscented Kalman filter (UKF), particle filter (PF), and unscented particle filter (UPF) for nonlinearon-Gaussian (or Gaussian) tracking problems, we apply this filter for IEEE 802.11 WLANs. GMSPPF provides a more viable means for tracking in any conditions the number of competing stations in IEEE 802.11 WLANs relative to EKF, UKF, PF, and UPF. Further, GMSPPF presents both high accuracy as well as prompt reactivity to changes in the network occupancy status. For the more accurate method (GMSPPF), the combined access mode is shown to maximize the system throughput by switching between the basic access mode and the RTS/CTS access mode.
机译:这封信提出了一种新的方法来估计IEEE 802.11网络中竞争站点的数量。由于测量模型的非线性/非高斯性质,本文提出了一种称为高斯混合西格玛点粒子滤波器(GMSPPF)的非线性滤波算法来估计竞争站点的数量。由于GMSPPF代表了传统扩展卡尔曼滤波器(EKF),无味卡尔曼滤波器(UKF),粒子滤波器(PF)和无味粒子滤波器(UPF)的更好的替代方案,因此可以解决非线性/非高斯(或高斯)跟踪问题。将此过滤器应用于IEEE 802.11 WLAN。 GMSPPF提供了一种更可行的方法,用于在任何情况下跟踪与EKF,UKF,PF和UPF相对的IEEE 802.11 WLAN中竞争站点的数量。此外,GMSPPF不仅具有很高的准确性,而且还可以迅速响应网络占用状态的变化。对于更精确的方法(GMSPPF),组合访问模式显示为通过在基本访问模式和RTS / CTS访问模式之间切换来最大化系统吞吐量。

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